Supplementary Results
Total Page：16
File Type：pdf, Size：1020Kb
Load more
Recommended publications
-
1 Evidence for Gliadin Antibodies As Causative Agents in Schizophrenia
1 Evidence for gliadin antibodies as causative agents in schizophrenia. C.J.Carter PolygenicPathways, 20 Upper Maze Hill, Saint-Leonard’s on Sea, East Sussex, TN37 0LG [email protected] Tel: 0044 (0)1424 422201 I have no fax Abstract Antibodies to gliadin, a component of gluten, have frequently been reported in schizophrenia patients, and in some cases remission has been noted following the instigation of a gluten free diet. Gliadin is a highly immunogenic protein, and B cell epitopes along its entire immunogenic length are homologous to the products of numerous proteins relevant to schizophrenia (p = 0.012 to 3e-25). These include members of the DISC1 interactome, of glutamate, dopamine and neuregulin signalling networks, and of pathways involved in plasticity, dendritic growth or myelination. Antibodies to gliadin are likely to cross react with these key proteins, as has already been observed with synapsin 1 and calreticulin. Gliadin may thus be a causative agent in schizophrenia, under certain genetic and immunological conditions, producing its effects via antibody mediated knockdown of multiple proteins relevant to the disease process. Because of such homology, an autoimmune response may be sustained by the human antigens that resemble gliadin itself, a scenario supported by many reports of immune activation both in the brain and in lymphocytes in schizophrenia. Gluten free diets and removal of such antibodies may be of therapeutic benefit in certain cases of schizophrenia. 2 Introduction A number of studies from China, Norway, and the USA have reported the presence of gliadin antibodies in schizophrenia 1-5. Gliadin is a component of gluten, intolerance to which is implicated in coeliac disease 6. -
Down-Regulation of Stem Cell Genes, Including Those in a 200-Kb Gene Cluster at 12P13.31, Is Associated with in Vivo Differentiation of Human Male Germ Cell Tumors
Research Article Down-Regulation of Stem Cell Genes, Including Those in a 200-kb Gene Cluster at 12p13.31, Is Associated with In vivo Differentiation of Human Male Germ Cell Tumors James E. Korkola,1 Jane Houldsworth,1,2 Rajendrakumar S.V. Chadalavada,1 Adam B. Olshen,3 Debbie Dobrzynski,2 Victor E. Reuter,4 George J. Bosl,2 and R.S.K. Chaganti1,2 1Cell Biology Program and Departments of 2Medicine, 3Epidemiology and Biostatistics, and 4Pathology, Memorial Sloan-Kettering Cancer Center, New York, New York Abstract on the degree and type of differentiation (i.e., seminomas, which Adult male germ cell tumors (GCTs) comprise distinct groups: resemble undifferentiated primitive germ cells, and nonseminomas, seminomas and nonseminomas, which include pluripotent which show varying degrees of embryonic and extraembryonic embryonal carcinomas as well as other histologic subtypes patterns of differentiation; refs. 2, 3). Nonseminomatous GCTs are exhibiting various stages of differentiation. Almost all GCTs further subdivided into embryonal carcinomas, which show early show 12p gain, but the target genes have not been clearly zygotic or embryonal-like differentiation, yolk sac tumors and defined. To identify 12p target genes, we examined Affymetrix choriocarcinomas, which exhibit extraembryonal forms of differ- (Santa Clara, CA) U133A+B microarray (f83% coverage of 12p entiation, and teratomas, which show somatic differentiation along genes) expression profiles of 17 seminomas, 84 nonseminoma multiple lineages (3). Both seminomas and embryonal carcinoma GCTs, and 5 normal testis samples. Seventy-three genes on 12p are known to express stem cell markers, such as POU5F1 (4) and were significantly overexpressed, including GLUT3 and REA NANOG (5). -
HNF6 Antibody (R31338)
HNF6 Antibody (R31338) Catalog No. Formulation Size R31338 0.5mg/ml if reconstituted with 0.2ml sterile DI water 100 ug Bulk quote request Availability 1-3 business days Species Reactivity Human, Mouse, Rat Format Antigen affinity purified Clonality Polyclonal (rabbit origin) Isotype Rabbit IgG Purity Antigen affinity Buffer Lyophilized from 1X PBS with 2.5% BSA and 0.025% sodium azide/thimerosal UniProt Q9UBC0 Applications Western blot : 0.5-1ug/ml IHC (FFPE) : 0.5-1ug/ml IHC (Frozen) : 0.5-1ug/ml Immunocytochemistry : 0.5-1ug/ml Limitations This HNF6 antibody is available for research use only. Western blot testing of HNF6 antibody and Lane 1: rat liver; 2: mouse liver; 3: human HeLa cell lysate. Expected/observed size ~51KD IHC-P: HNF6 antibody testing of human liver cancer tissue ICC testing of HNF6 antibody and HCT116 cells IHC-F testing of rat liver tissue IHC-P testing of rat liver tissue Description One cut homeobox 1 (ONECUT1), also called Hepatocyte nuclear factor 6 (HNF6) is found strong expression in liver and lower expression in testis and skin. The gene encodes a member of the Cut homeobox family of transcription factors. Expression of the encoded protein is enriched in the liver, where it stimulates transcription of liver-expressed genes, and antagonizes glucocorticoid-stimulated gene transcription. This gene may influence a variety of cellular processes including glucose metabolism, cell cycle regulation, and it may also be associated with cancer. Application Notes The stated application concentrations are suggested starting amounts. Titration of the HNF6 antibody may be required due to differences in protocols and secondary/substrate sensitivity. -
Derivation of Stable Microarray Cancer-Differentiating Signatures Using Consensus Scoring of Multiple Random Sampling and Gene-Ranking Consistency Evaluation
Research Article Derivation of Stable Microarray Cancer-Differentiating Signatures Using Consensus Scoring of Multiple Random Sampling and Gene-Ranking Consistency Evaluation Zhi Qun Tang,1,2 Lian Yi Han,1,2 Hong Huang Lin,1,2 Juan Cui,1,2 Jia Jia,1,2 Boon Chuan Low,2,3 Bao Wen Li,2,4 and Yu Zong Chen1,2 1Bioinformatics and Drug Design Group, Department of Pharmacy; 2Center for Computational Science and Engineering; and Departments of 3Biological Sciences and 4Physics, National University of Singapore, Singapore, Singapore Abstract sampling methods. Only 1 to 5 of the 4 to 60 selected predictor Microarrays have been explored for deriving molecular genes in each of these sets are present in more than half of the signatures to determine disease outcomes, mechanisms, other nine sets (Table 1), and 2 to 20 of the predictor genes in each targets, and treatment strategies. Although exhibiting good set are cancer related (Table 2). Despite the use of sophisticated predictive performance, some derived signatures are unstable class differentiation and signature selection methods, the selected due to noises arising from measurement variability and signatures show few overlapping predictor genes, as in the case of biological differences. Improvements in measurement, anno- other microarray data sets including non–Hodgkin lymphoma, tation, and signature selection methods have been proposed. acute lymphocytic leukemia, breast cancer, lung adenocarcinoma, We explored a new signature selection method that incorpo- medulloblastoma, hepatocellular carcinoma, and acute myeloid rates consensus scoring of multiple random sampling and leukemia (9, 15). multistep evaluation of gene-ranking consistency for maxi- Although these signatures display high cancer differentiation mally avoiding erroneous elimination of predictor genes. -
EXTENDED MATERIALS and METHODS Animal Experimentation. All Experiments Were Performed in Agreement with the Swiss Law on Animal
EXTENDED MATERIALS AND METHODS Animal experimentation. All experiments were performed in agreement with the Swiss law on animal protection (LPA), under license No GE 81/14 (to DD). In situ hybridization. Whole mount in situ hybridizations were performed as described in (Woltering et al., 2014). Probes for the Hoxa11, Hoxa13, Hoxd8, Hoxd10, Hoxd12, Hoxd13 and Evx2 genes were synthetized and purified as previously reported (Herault et al., 1996; Woltering et al., 2014). Plasmids encoding the cDNAs of the Prrx2 and Dbx2 genes were purchased from Addgene and probes were synthetized as previously reported (Pierani et al., 1999; Stelnicki et al., 1998). Right or left forelimbs were dissected from stained embryos and photographied dorsally with a Leica MZ16 stereomicroscope. Pictures from left forelimbs are displayed inverted. RNA extraction. Total RNA was extracted from individual pairs of either wild type or double Hox13-/- mutant proximal and distal forelimb buds, using the RNeasy Micro Kit (Qiagen) following manufacturer instructions. A total of 100ng of pure total RNA was amplified following standard Illumina procedure for polyA-selected RNA. RNA-seq data generation. RNA sequencing (RNA-seq) libraries were prepared with the Illumina TruSeq Stranded mRNA protocol and sequenced on a HiSeq 2500 machine, as single-end, 100 base pairs (bp) reads. The preparation of libraries and sequencing were performed by the genomic platform of the University of Geneva. RNA-seq data analysis. A mutant version of the genome, encoding the Hoxd13/LacZ and the Hoxa13/Neo+ alleles (Fromental-Ramain et al., 1996; Kondo et al., 1998), was assembled and annotated and used as reference genome to map the Hoxa13-/- and Hoxd13-/- RNA-seq data. -
Olig2 and Ngn2 Function in Opposition to Modulate Gene Expression in Motor Neuron Progenitor Cells
Downloaded from genesdev.cshlp.org on September 29, 2021 - Published by Cold Spring Harbor Laboratory Press Olig2 and Ngn2 function in opposition to modulate gene expression in motor neuron progenitor cells Soo-Kyung Lee,1 Bora Lee,1 Esmeralda C. Ruiz, and Samuel L. Pfaff2 Gene Expression Laboratory, The Salk Institute for Biological Studies, La Jolla, California 92037, USA Spinal motor neurons and oligodendrocytes are generated sequentially from a common pool of progenitors termed pMN cells. Olig2 is a bHLH-class transcription factor in pMN cells, but it has remained unclear how its transcriptional activity is modulated to first produce motor neurons and then oligodendrocytes. Previous studies have shown that Olig2 primes pMN cells to become motor neurons by triggering the expression of Ngn2 and Lhx3. Here we show that Olig2 also antagonizes the premature expression of post-mitotic motor neuron genes in pMN cells. This blockade is counteracted by Ngn2, which accumulates heterogeneously in pMN cells, thereby releasing a subset of the progenitors to differentiate and activate expression of post-mitotic motor neuron genes. The antagonistic relationship between Ngn2 and Olig2 is mediated by protein interactions that squelch activity as well as competition for shared DNA-binding sites. Our data support a model in which the Olig2/Ngn2 ratio in progenitor cells serves as a gate for timing proper gene expression during the development of pMN cells: Olig2high maintains the pMN state, thereby holding cells in reserve for oligodendrocyte generation, whereas Ngn2high favors the conversion of pMN cells into post-mitotic motor neurons. [Keywords: Motor neuron; oligodendrocyte; development; basic helix–loop–helix (bHLH); neurogenin (Ngn); Olig] Supplemental material is available at http://www.genesdev.org. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
![Pdf Sub-Classification of Patients with a Molecular Alteration Provides Better Response [57]](https://docslib.b-cdn.net/cover/8649/pdf-sub-classification-of-patients-with-a-molecular-alteration-provides-better-response-57-268649.webp)
Pdf Sub-Classification of Patients with a Molecular Alteration Provides Better Response [57]
Theranostics 2021, Vol. 11, Issue 12 5759 Ivyspring International Publisher Theranostics 2021; 11(12): 5759-5777. doi: 10.7150/thno.57659 Research Paper Homeobox B5 promotes metastasis and poor prognosis in Hepatocellular Carcinoma, via FGFR4 and CXCL1 upregulation Qin He1, Wenjie Huang2, Danfei Liu1, Tongyue Zhang1, Yijun Wang1, Xiaoyu Ji1, Meng Xie1, Mengyu Sun1, Dean Tian1, Mei Liu1, Limin Xia1 1. Department of Gastroenterology, Institute of Liver and Gastrointestinal Diseases, Hubei Key Laboratory of Hepato-Pancreato-Biliary Diseases, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei Province, China. 2. Hubei Key Laboratory of Hepato-Pancreato-Biliary Diseases; Hepatic Surgery Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology; Clinical Medicine Research Center for Hepatic Surgery of Hubei Province; Key Laboratory of Organ Transplantation, Ministry of Education and Ministry of Public Health, Wuhan, Hubei, 430030, China. Corresponding author: Dr. Limin Xia, Department of Gastroenterology, Institute of Liver and Gastrointestinal Diseases, Hubei Key Laboratory of Hepato-Pancreato-Biliary Diseases, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei Province, China; Phone: 86 27 6937 8507; Fax: 86 27 8366 2832; E-mail: [email protected]. © The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions. Received: 2020.12.29; Accepted: 2021.03.17; Published: 2021.03.31 Abstract Background: Since metastasis remains the main reason for HCC-associated death, a better understanding of molecular mechanism underlying HCC metastasis is urgently needed. -
Figure S1. Representative Report Generated by the Ion Torrent System Server for Each of the KCC71 Panel Analysis and Pcafusion Analysis
Figure S1. Representative report generated by the Ion Torrent system server for each of the KCC71 panel analysis and PCaFusion analysis. (A) Details of the run summary report followed by the alignment summary report for the KCC71 panel analysis sequencing. (B) Details of the run summary report for the PCaFusion panel analysis. A Figure S1. Continued. Representative report generated by the Ion Torrent system server for each of the KCC71 panel analysis and PCaFusion analysis. (A) Details of the run summary report followed by the alignment summary report for the KCC71 panel analysis sequencing. (B) Details of the run summary report for the PCaFusion panel analysis. B Figure S2. Comparative analysis of the variant frequency found by the KCC71 panel and calculated from publicly available cBioPortal datasets. For each of the 71 genes in the KCC71 panel, the frequency of variants was calculated as the variant number found in the examined cases. Datasets marked with different colors and sample numbers of prostate cancer are presented in the upper right. *Significantly high in the present study. Figure S3. Seven subnetworks extracted from each of seven public prostate cancer gene networks in TCNG (Table SVI). Blue dots represent genes that include initial seed genes (parent nodes), and parent‑child and child‑grandchild genes in the network. Graphical representation of node‑to‑node associations and subnetwork structures that differed among and were unique to each of the seven subnetworks. TCNG, The Cancer Network Galaxy. Figure S4. REVIGO tree map showing the predicted biological processes of prostate cancer in the Japanese. Each rectangle represents a biological function in terms of a Gene Ontology (GO) term, with the size adjusted to represent the P‑value of the GO term in the underlying GO term database. -
Supplemental Materials ZNF281 Enhances Cardiac Reprogramming
Supplemental Materials ZNF281 enhances cardiac reprogramming by modulating cardiac and inflammatory gene expression Huanyu Zhou, Maria Gabriela Morales, Hisayuki Hashimoto, Matthew E. Dickson, Kunhua Song, Wenduo Ye, Min S. Kim, Hanspeter Niederstrasser, Zhaoning Wang, Beibei Chen, Bruce A. Posner, Rhonda Bassel-Duby and Eric N. Olson Supplemental Table 1; related to Figure 1. Supplemental Table 2; related to Figure 1. Supplemental Table 3; related to the “quantitative mRNA measurement” in Materials and Methods section. Supplemental Table 4; related to the “ChIP-seq, gene ontology and pathway analysis” and “RNA-seq” and gene ontology analysis” in Materials and Methods section. Supplemental Figure S1; related to Figure 1. Supplemental Figure S2; related to Figure 2. Supplemental Figure S3; related to Figure 3. Supplemental Figure S4; related to Figure 4. Supplemental Figure S5; related to Figure 6. Supplemental Table S1. Genes included in human retroviral ORF cDNA library. Gene Gene Gene Gene Gene Gene Gene Gene Symbol Symbol Symbol Symbol Symbol Symbol Symbol Symbol AATF BMP8A CEBPE CTNNB1 ESR2 GDF3 HOXA5 IL17D ADIPOQ BRPF1 CEBPG CUX1 ESRRA GDF6 HOXA6 IL17F ADNP BRPF3 CERS1 CX3CL1 ETS1 GIN1 HOXA7 IL18 AEBP1 BUD31 CERS2 CXCL10 ETS2 GLIS3 HOXB1 IL19 AFF4 C17ORF77 CERS4 CXCL11 ETV3 GMEB1 HOXB13 IL1A AHR C1QTNF4 CFL2 CXCL12 ETV7 GPBP1 HOXB5 IL1B AIMP1 C21ORF66 CHIA CXCL13 FAM3B GPER HOXB6 IL1F3 ALS2CR8 CBFA2T2 CIR1 CXCL14 FAM3D GPI HOXB7 IL1F5 ALX1 CBFA2T3 CITED1 CXCL16 FASLG GREM1 HOXB9 IL1F6 ARGFX CBFB CITED2 CXCL3 FBLN1 GREM2 HOXC4 IL1F7 -
TF Activation Profiling Plate Array II Signosis, Inc
Signosis, Inc. Innovative Plate Assay Solutions TF Activation Profiling Plate Array II Catalog Number: FA-1002 (For Research Use Only) Introduction Materials Provided with the Kit Transcription factors (TFs) are a group of cellular proteins that play essential roles in regulating gene Component Qty Store at expression. They act as sensors to monitor cellular 96-Well Plates (with 2 RT changes and convert signals into gene expression. aluminum adhesive seal) Often, a specific cellular signal pathway can activate Isolation Columns 2 RT multiple TFs. The expression of a specific gene can Elution Buffer 400µL RT also be under the control of multiple TFs. Thus, TF Plate Hybridization Buffer 20mL RT monitoring the activation of multiple TFs 5X Plate Hybridization Wash 60mL RT simultaneously is critical to understanding the Buffer molecular mechanism of cellular regulation underlying 5X Detection Wash Buffer 60mL RT cell signaling and gene expression. Signosis, Inc.’s TF Blocking Buffer 60mL RT Activation Profiling Plate Array II is used for Filter Wash Buffer 5mL 4°C monitoring 96 different TFs simultaneously from one Filter Binding Buffer 1mL 4°C sample. Substrate A 2mL 4°C Substrate B 2mL 4°C Principle of the assay Streptavidin-HRP Conjugate 40µL 4°C Substrate Dilution Buffer 16mL 4°C Signosis, Inc.’s TF Activation Profiling Plate Array II TF Binding Buffer Mix 60µL -20°C is used for monitoring the activation of multiple TFs TF Probe Mix II 20µL -20°C simultaneously. With this technology a series of biotin-labeled probes are made based on the consensus sequences of TF DNA-binding sites. -
UNIVERSITY of CALIFORNIA, IRVINE Combinatorial Regulation By
UNIVERSITY OF CALIFORNIA, IRVINE Combinatorial regulation by maternal transcription factors during activation of the endoderm gene regulatory network DISSERTATION submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in Biological Sciences by Kitt D. Paraiso Dissertation Committee: Professor Ken W.Y. Cho, Chair Associate Professor Olivier Cinquin Professor Thomas Schilling 2018 Chapter 4 © 2017 Elsevier Ltd. © 2018 Kitt D. Paraiso DEDICATION To the incredibly intelligent and talented people, who in one way or another, helped complete this thesis. ii TABLE OF CONTENTS Page LIST OF FIGURES vii LIST OF TABLES ix LIST OF ABBREVIATIONS X ACKNOWLEDGEMENTS xi CURRICULUM VITAE xii ABSTRACT OF THE DISSERTATION xiv CHAPTER 1: Maternal transcription factors during early endoderm formation in 1 Xenopus Transcription factors co-regulate in a cell type-specific manner 2 Otx1 is expressed in a variety of cell lineages 4 Maternal otx1 in the endodermal conteXt 5 Establishment of enhancers by maternal transcription factors 9 Uncovering the endodermal gene regulatory network 12 Zygotic genome activation and temporal control of gene eXpression 14 The role of maternal transcription factors in early development 18 References 19 CHAPTER 2: Assembly of maternal transcription factors initiates the emergence 26 of tissue-specific zygotic cis-regulatory regions Introduction 28 Identification of maternal vegetally-localized transcription factors 31 Vegt and OtX1 combinatorially regulate the endodermal 33 transcriptome iii